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The main workable coal measures are concentrated at two horizons within the Miocene Muara Enim Formations (MEF). The main Coal Bed Methane (CBM) targets are the MEF coals, which are known to have good coal thickness and favorable depth for CBM production. Typically, coals are recognized to thin toward the east as they pinch out against the Sunda landmass. Important elements of the CBM play are coal presence and coal lateral distribution. The objective of this study is to identify thin coal reservoir distribution by using well and seismic data integration. Reprocessing seismic data prior to acoustic impedance (AI) inversion produces better results. In situations where wells are located far from seismic lines, calibration with logs is problematic and inversion produces less than maximum results. Multi-attribute approach can optimize the results. Integration of the filtering, AI inversion, and then multi-attribute & neural network methods produce the best output to identify coal seams, their distribution and continuity. The thickest coal identified well data (10 wells) of 6 m in depth 768 m with a total of 5 layers of coal (seam A, B, C, D, and E) in R5 well. Based on seismic modeling, the seams was only seams A with a total volume respectively 518 million m3.